The present disclosure relates to a system and method for providing decision support. More particularly, the present disclosure relates to a system and method for providing decision support, using precursor networks to predict an event.
Many events of significance (Consequent Events) are preceded by a network of other events that have geospatial and time relationships both to one another and to a particular Consequent Event that they precede (each of such other events being a Precursor Activity and the network of such Precursor Activities being a Precursor Activity Network).
In many cases, the relationships among specific Precursor Activities that constitute a Precursor Activity Network and between a Precursor Activity Network and the Consequent Event that it precedes can be documented by, or from information gathered from, subject matter experts (SMEs). In some cases, such documentation has consisted of studies or scholarly works (see, for example, the study funded by the U.S. Department of Justice entitled “Pre-Incident Indicators of Terrorist Incidents: The Identification of Behavioral, Geographic, and Temporal Patterns of Preparatory Conduct” by Brent L. Smith, Kelly R. Damphousse, and Paxton Roberts, Terrorism Research Center in Fulbright College, University of Arkansas).
Presently, the Precursor Activities are manually documented and searched against suspect events, which renders real time or near real time alert of certain events impossible or impracticable. Accordingly, there is a need to establish an automated method and system so as to quickly search for precursor activities, identify evolving Consequent Events, and provide alerts to users on a real time or near real time basis.